Mine earthquake early warning method, device and system based on micro-earthquake monitoring

Abstract

The invention relates to a mine earthquake early warning method based on micro-earthquake monitoring, and the method comprises the steps: converting a monitoring signal at a current moment from a time domain to a frequency domain through Fourier transform, and obtaining the frequency point data at the current moment; and judging whether the monitoring frequency point data at the current moment is normal or not according to whether the change amplitude of the energy value of the time frequency point data at the current moment and the energy value of the stored background field frequency point data at the current moment exceeds a set threshold value or not, thereby judging whether a micro-seismic event occurs or not, and determining the position of the micro-seismic event. According to the mine earthquake early warning method, by updating the background field frequency point data in real time, other gentle background field changes except the sudden micro earthquake time can be ignored in the monitoring process, the generated tiny changes are added into the background field in time, the effect of continuously suppressing noise is achieved, and early warning judgment is more accurate.

Description

Technical Field

[0001] The present invention relates to the field of metal mine earthquake monitoring, and in particular to a mine earthquake early warning method based on microseismic monitoring. Background Art

[0002] Mine tremors are seismic activity caused by mining operations and are the most dangerous of all induced earthquakes. When a mine tremor occurs, the surrounding rock underground rapidly releases energy, often causing sudden destruction of underground tunnels or mining faces, ground shaking, damage to buildings, and, in severe cases, casualties. Mine tremors are also one of the most difficult phenomena to understand in deep mining operations worldwide. Their characteristics vary depending on the type of mine and the focal mechanism. Mine tremors in metal mines are more likely to be caused by fault activity, and their characteristics are more similar to those of natural earthquakes.

[0003] Currently, the main detection methods for monitoring and early warning of metal mine earthquakes are geophysical exploration and microseismic location. Geophysical exploration requires a large number of geophones, resulting in cumbersome deployment and significant data acquisition costs. Geological imaging technology is relatively backward, making it incapable of real-time and rapid imaging of underground structures. Furthermore, the acquisition stations are relatively primitive, hindering remote data communication and remote, real-time batch imaging, resulting in poor monitoring and early warning effectiveness. Microseismic location, when used to locate earthquake sources, is susceptible to signal obscuration or interference from surrounding noise due to its low energy and short duration. For example, most microseismic events occur at frequencies between 200 and 1500 Hz, with energy levels ranging from -3 to +1 on the Richter scale and typically lasting less than a second. Furthermore, absorption effects of rock and other media can affect the energy during propagation, making it difficult to detect after propagating for a certain distance. Consequently, microseismic signals collected using traditional time-domain data acquisition and amplitude stacking methods are weak and susceptible to various interferences, resulting in poor signal processing and inaccurate location.

[0004] Because the Earth's magnetic field naturally varies slightly over time, significant differences between the early and late stages of a long-term monitoring project can mask unexpected microseismic events. To mitigate the effects of these temporal variations, the real-time geomagnetic signals must be regularly corrected. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide a mine earthquake early warning method based on microseismic monitoring, which has the advantage of being able to correct the collected geomagnetic signals in real time to obtain microseismic signals with better accuracy and higher quality. It can effectively eliminate the noise interference of the geological background field and improve the sensitivity and accuracy of microseismic positioning, thereby being able to issue more accurate mine earthquake early warning signals.

[0006] A metal mine earthquake early warning method based on microseismic monitoring comprises the following steps:

[0007] S10 converts the input current monitoring signal from the time domain to the frequency domain to obtain the current monitoring frequency data;

[0008] S20 determines whether the current monitoring frequency data is normal based on whether the change amplitude between the energy value of the current monitoring frequency data and the energy value of the stored background field frequency data at the current moment exceeds a set threshold:

[0009] When the change amplitude does not exceed the threshold, executing step S30;

[0010] When the change amplitude exceeds the threshold, step S40 is executed;

[0011] S30 determines that the monitoring frequency data at the current moment is normal, and performs weighted processing on the monitoring frequency data at the current moment and the stored background frequency data at the current moment to obtain the background frequency data at the next moment, and updates the background frequency data at the next moment to the background frequency data set, and continues the monitoring signal analysis at the next moment;

[0012] S40 does not update the background frequency data and evaluates the monitoring frequency data at the current moment: if the change amplitude exceeds the threshold value intermittently or occasionally, the monitoring frequency data at the current moment is determined to be normal, the monitoring data at the current moment is ignored, and the monitoring signal analysis at the next moment is continued; if the change amplitude exceeds the threshold value continuously or occurs multiple times at intervals, the monitoring frequency data at the current moment is determined to be abnormal, and an abnormal signal is output;

[0013] S50 uses positioning technology to determine the location of the micro-earthquake based on the input abnormal signal and sends an early warning signal to the place where the micro-earthquake occurred.

[0014] The mine earthquake early warning method described in the present invention, by updating the background field frequency data in real time, can ignore other relatively gentle background field changes except for the time of sudden micro-earthquakes during monitoring, and promptly add the small changes that have occurred to the background field, so as to achieve the effect of continuously suppressing noise, make the early warning judgment more accurate, and reduce the risk of misjudgment and wrong judgment.

[0015] Furthermore, the background field frequency data is obtained by:

[0016] S21 obtains initial background field frequency point data: performs Fourier transform on the monitoring signals collected during a certain period of time without microseismic events in the early stage to obtain initial background field frequency point data;

[0017] S22 obtains the background field frequency data at the current moment: the monitoring frequency data at the previous moment and the background field frequency data at the previous moment are weighted averaged to obtain the background field frequency data at the current moment, which is expressed as:

[0018]

[0019] in, Indicates the background frequency data at the current moment. Indicates the background frequency data at the previous moment, Indicates the frequency data monitored at the last moment. During the acquisition process, the frequency amplitude change caused by changes in the natural geological background will not exceed the threshold. Frequency weighting can be used to update the background field data more smoothly.

[0020] Furthermore, before converting the input current-time monitoring signal from the time domain to the frequency domain, the method further includes performing point-by-point time-varying correction on the current-time monitoring signal using the input timing geological background field noise signal, wherein the current-time monitoring signal after time-varying correction satisfies the following relationship:

[0021]

[0022] in, is the current monitoring signal after time-varying correction, is the monitoring signal at the current moment, R (t′-1)～t′ is the time-varying correction from the previous period to the current period;

[0023] The time-varying correction value R from the previous period to the current period (t′-1)～t′ Satisfies the following relationship:

[0024]

[0025] in, is the amplitude sequence of the geological background noise signal in the initial period, The amplitude sequence of the geological background noise signal over the previous period. Because the frequency and amplitude of the energy collected by the collector vary over time, time-varying correction can calibrate data collected on different dates to the same baseline level. The background field weighting employed takes into account that even without microseismic events, strata can slowly shift due to tectonic movement. This normal, slow shift is recorded by continuously weighting and updating the background field. This ensures that microseismic events can be detected while preventing tectonic shifts accumulated over time from triggering false alarms.

[0026] At the same time, the present invention provides a mine earthquake early warning system based on microseismic monitoring, including multiple data acquisition units, a data exchange unit and a monitoring host. The signals collected by the data acquisition units are transmitted to the monitoring host via the data exchange unit, and the monitoring host executes the steps of the above-mentioned mine earthquake early warning method based on microseismic monitoring, wherein the data acquisition unit includes multiple signal collectors and a POE power supply to power the signal collectors.

[0027] Furthermore, a global consistency correction is performed on the signal collector to obtain a global consistency correction coefficient of the signal collector. The global consistency correction coefficient is obtained by the following method:

[0028] All signal collectors are placed at the same point to collect data for a period of time, and the average signal amplitude of each signal collector and the average signal amplitude of all signal collectors are obtained;

[0029] Calculate the ratio of the average amplitude of all signal collectors to the average amplitude of each signal collector to obtain the global consistency correction coefficient c of each signal collector. i , whose expression is:

[0030]

[0031] Where E is the average amplitude of all signal collectors, is the average amplitude of the i-th signal collector, A i [x j ] is the amplitude sequence of the signal collected by the i-th signal collector, m is the number of signals collected by the i-th signal collector, and n is the number of signal collectors. Using global consistency correction to calibrate the collectors' global consistency coefficients eliminates systematic errors introduced by collector differences, making subsequent signal processing and evaluation more accurate. Furthermore, combining global consistency correction with time-varying correction can better eliminate the impact of non-microseismic events on imaging, ensuring that changes in imaging results primarily reflect changes in underground structure, rather than being affected by different instruments or dates, resulting in more reliable monitoring results.

[0032] For better understanding and implementation, the present invention is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a schematic diagram of a mine earthquake early warning system based on microseismic monitoring;

[0034] Figure 2 Flowchart for preprocessing the acquired signal using global consistency correction and time-varying correction;

[0035] Figure 3 This is a flow chart of the mine earthquake early warning method based on microseismic monitoring. DETAILED DESCRIPTION

[0036] The technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiments of the present invention.

[0037] (1) Mine earthquake early warning system

[0038] See also Figure 1The mine earthquake early warning system based on microseismic monitoring designed by the present invention has a tree topology structure, which includes: multiple data acquisition units 10, a data exchange unit 20 and a monitoring host 30, wherein the data acquisition unit 10 is connected to the monitoring host 30 through the data exchange unit 20, and the monitoring host includes a processor (not shown in the figure) and a memory (not shown in the figure).

[0039] Specifically, the data acquisition unit 10 includes multiple signal collectors 12 and a POE power supply 14 that supplies power to the signal collectors. Each signal collector 12 consists of a detector 122 connected in series with a POE repeater 124. Furthermore, the detector 124 is an independent IP device, including a sensor (not shown) and an acquisition circuit (not shown). The sensor uses a three-axis MEMS accelerometer with orthogonal axes, which collects data from all three axes during monitoring. The acquisition circuit includes two external network ports. Based on the TCP / IP protocol, each detector can independently communicate with the monitoring host 30 or any PC connected to the data exchange unit 20, enabling real-time data acquisition and transmission.

[0040] The data exchange unit 20 is a network switch, which connects all POE power supplies 14 and aggregates the signals of multiple POEs to transmit the data to the monitoring host 30 .

[0041] (2) Preprocessing of the signal collector 12

[0042] In order to eliminate the systematic errors caused by differences in signal collectors and make subsequent signal processing and evaluation more accurate, all signal collectors must be globally aligned before deployment. The specific global alignment alignment method is as follows:

[0043] 1) Place all signal collectors at the same point to collect data for a period of time and obtain the average amplitude of each signal collector;

[0044] 2) By calculating the average amplitude of all signal collectors, a global consistency correction coefficient of each signal collector is obtained, wherein the global consistency correction coefficient refers to the ratio of the average amplitude of all signal collectors in the monitored mining area to the average amplitude of each signal collector.

[0045] Specifically, the mining area to be monitored needs to be equipped with n signal collectors A1, A2, ...A n , each signal collector performs m acquisitions x1, x2, ... x m , then the amplitude sequence of the signal collected by the i-th signal collector is A i [x1],A i [x2],...A i [x m], the amplitude sequence of the global signal is The average amplitude value of the i-th signal collector Satisfy formula (1):

[0046]

[0047] The global average amplitude value E satisfies formula (2):

[0048]

[0049] Then the global consistency correction coefficient of the i-th signal collector is shown in formula (3):

[0050]

[0051] Then the monitoring signal collected by the i-th signal collector satisfies the following after being corrected by the global consistency correction coefficient:

[0052] CA i [x]=A i [x]*c i (4)

[0053] (4) In the formula, CA i [x] represents the amplitude sequence of the monitoring signal of the i-th collector corrected by the global consistency correction coefficient, A i [x] represents the amplitude sequence of the original monitoring signal of the i-th collector, c i represents the global consistency correction coefficient of the i-th collector.

[0054] (3) Preprocessing of collected signals

[0055] In order to eliminate the influence of slow changes in strata caused by geological tectonic movements other than microseismic events on monitoring results and obtain more accurate monitoring signals, time-varying correction can be performed on the signals collected by the signal collector. The specific correction method is described below.

[0056] First, deploy the signal collectors in the mining area to be monitored in the following manner:

[0057] 1) One of the signal collectors is placed as a base station in an area of the mining area to be monitored where the strata are relatively stable and can remain stable for a long time, and is used to regularly collect periodic signals of geomagnetic changes to obtain the amplitude sequence A0[x] of the regular geological background field noise signal in the area to be monitored;

[0058] 2) The remaining signal collectors are used as monitoring stations and are arranged in the areas of high microseismic activity that need to be monitored in the mining area according to the layout plan. They are used to collect microseismic monitoring signals in real time and obtain the amplitude sequence A of the real-time monitoring signal of the monitored area. i [x].

[0059] Then, the real-time monitoring signal is corrected point by point by the timing geological background noise signal to obtain the real-time monitoring signal RA after deducting the background noise signal. i [x]. The specific time-varying correction method is as follows:

[0060] 1) Calculate the time-varying correction amount from the time period t′-1 to the time period t′ corresponding to the monitoring signal at time t.

[0061] The amplitude sequence of the geological background noise signal is A0[x1], A0[x2], ..., A0[x m ], and its amplitude sequence in the initial period is Its amplitude sequence in the t′-1 period is The root mean square S of the amplitude sequence in the initial period and t′-1 period is 0 and S t′-1 satisfy:

[0062]

[0063] Then the time-varying correction value R from period t′-1 to period t′ is (t′-1)～t′ satisfy:

[0064]

[0065] 2) According to the time-varying correction amount from time t′-1 to time t′, the monitoring signal at time t is corrected point by point to obtain the monitoring signal at time t after deducting the background field noise signal, that is, the monitoring signal at the current moment after deducting the background field noise signal

[0066] Specifically, during the time period from t′-1 to t′, the i-th signal collector collected data p times in total. The time-varying correction values corresponding to the microseismic signals at tp,..., t-2, t-1, and t are all R (t′-1)～t′ For the amplitude sequence of the monitoring signal collected by the i-th signal collector at time t Divide by the corresponding time-varying correction R (t′-1)～t′ , we can get the amplitude sequence of the monitoring signal at time t after deducting the geological background noise signal That is, the current monitoring signal after deducting the background field noise signal Satisfying formula (8):

[0067]

[0068] In this embodiment, the signal collector is globally consistent and the monitoring signal collected by the i-th signal collector at time t is corrected point by point to obtain the real-time monitoring signal R after deducting the background field noise signal.c A i [x]. The specific time-varying correction method is as follows:

[0069] S01 performs global consistency correction on the geological background field noise signal of the t′-1 period collected by the base station to obtain the geological background field noise signal of the t′-1 period after global consistency correction. The geological background field noise signal Satisfy (9 formula):

[0070]

[0071] (9) In formula, represents the amplitude sequence of the geological background noise signal in the period t′-1, and c0 represents the global consistency correction coefficient of the base station.

[0072] S02 calculates the time-varying correction amount CR from the time t′-1 to the time t′ corresponding to the monitoring signal at time t after global consistency correction (t′-1)～t′ , the time-varying correction CR (t′-1)～t′ Satisfying formula (10):

[0073]

[0074] In formula (10), It represents the amplitude sequence of the geological background noise signal of the initial period after global consistency correction, and its global consistency correction coefficient is c0.

[0075] S03 performs global consistency correction on the monitoring signal at time t collected by the monitoring station to obtain the monitoring signal at time t after global consistency correction. The monitoring signal satisfies formula (11).

[0076]

[0077] (11) In formula, represents the amplitude sequence of the monitoring signal at time t, c i represents the global consistency correction coefficient of the i-th signal collector.

[0078] S04 is the time-varying correction amount CR corrected by global consistency from period t′-1 to period t′ (t′-1)～t′ , the monitoring signal corrected by global consistency at time t Perform point-by-point time-varying correction to obtain the monitoring signal at time t after global consistency correction and subtraction of the background field noise signal The monitoring signal Satisfying formula (12):

[0079]

[0080] (4) Judgment and early warning of mine earthquakes

[0081] The monitoring host of the mine earthquake early warning system performs the set signal processing steps on the current time signal collected by the data acquisition unit at time t to complete the judgment and early warning of mine earthquake. The current time signal includes the monitoring signal corrected by global consistency or time-varying corrected monitoring signal Or the monitoring signal after global consistency correction and time variation correction Or the monitoring signal collected by the signal collector The set signal processing steps specifically include the following steps.

[0082] S10 converts the input monitoring signal at the current moment from the time domain to the frequency domain to obtain the monitoring frequency point data at the current moment.

[0083] This step uses Fourier transform to transform the current monitoring signal from the time domain to the frequency domain.

[0084] S20 determines whether the current monitoring frequency data is normal based on whether the change amplitude between the energy value of the current monitoring frequency data and the energy value of the stored background field frequency data at the current moment exceeds a set threshold. This step specifically includes the following sub-steps.

[0085] S21 obtains initial background field frequency data.

[0086] The current monitoring frequency data collected during a certain period of time without microseismic events is defined as the initial background frequency data of each signal collector And store the data in the background field frequency point data set. Satisfying formula (13):

[0087]

[0088] (13) is the amplitude sequence of the monitoring signal collected by the i-th signal collector during a certain period of time without microseismic events, where for or or or

[0089] Furthermore, under the premise of ensuring that there are no microseismic events in the early stage, data collection work of equal length is carried out for k times in different time periods, and the collected signals are Fourier transformed to obtain the background field frequency point data of the early period. Then the initial background field frequency point data of each signal collector satisfies formula (14).

[0090]

[0091] S22 obtains the monitoring frequency data at the current moment.

[0092] The current monitoring frequency data that is not used as the initial background field frequency data is determined as the current monitoring frequency data The current monitoring frequency data Satisfying formula (15):

[0093]

[0094] (15) is the amplitude sequence of the monitoring signal at the current moment collected by the i-th signal collector in the subsequent monitoring process, where for or or or

[0095] S23 calculates the change amplitude Δ between the energy value of the monitoring frequency data at the current moment and the energy value of the stored background frequency data at the current moment t .

[0096] Current monitoring frequency data The current background frequency data stored The change in energy value Δ t is calculated as follows:

[0097]

[0098] S24 compares the change amplitude Δ at the current moment t With the set threshold T t The size of , and based on the comparison result, determine whether the current monitoring frequency data is normal:

[0099] (1) If Δ t ≤T t , that is, when the change amplitude does not exceed the threshold, executing step S30;

[0100] (2) If Δ t >T t , that is, when the change amplitude exceeds the threshold, step S40 is executed.

[0101] S30 determines that the monitoring frequency data at the current moment is normal, and performs weighted processing on the monitoring frequency data at the current moment and the stored background field frequency data at the current moment to obtain the background field frequency data at the next moment, and updates the background field frequency data at the next moment to the background field frequency data set, and continues the monitoring signal analysis at the next moment.

[0102] Specifically, the current monitoring frequency data and the stored current background frequency data are used to calculate the background frequency data at the next moment using the weighted average method. And update it to the background field frequency data set for the next moment's monitoring frequency data judgment and continue the next moment's monitoring signal analysis.

[0103] Among them, the background field frequency data at the next moment is calculated as follows:

[0104]

[0105] S40 does not update the background field frequency data and evaluates the monitoring frequency data at the current moment: if the change amplitude exceeds the threshold and occurs intermittently or accidentally, it is determined that the monitoring frequency data at the current moment is normal, the monitoring data at the current moment is ignored, and the monitoring signal analysis at the next moment continues; if the change amplitude exceeds the threshold and occurs continuously or multiple times at intervals, it is determined that the monitoring frequency data at the current moment is abnormal, and an abnormal signal is output.

[0106] S50 uses positioning technology to determine the location of the micro-earthquake based on the input abnormal signal and sends an early warning signal to the place where the micro-earthquake occurred.

[0107] Specifically, the distances between all signal collectors and the microseismic source are calculated, and the location of the source can be accurately determined using positioning technology, where the distance between the microseismic source and the i-th signal collector satisfies formula (18):

[0108]

[0109] (18) Where V is the propagation velocity of seismic waves, f j is the resonant frequency of the j-th layer of medium at the location of the i-th signal collector.

[0110] Furthermore, the positioning technology may adopt a three-circle positioning method, a multi-site frequency resonance positioning method, and the like.

[0111] The present invention also provides a mine earthquake early warning device based on microseismic monitoring, comprising:

[0112] Data conversion module: used to convert the input current monitoring signal from the time domain to the frequency domain to obtain the current monitoring frequency data;

[0113] Judgment module: used to judge whether the current monitoring frequency data is normal based on whether the change amplitude of the energy value of the current monitoring frequency data and the energy value of the stored background field frequency data at the current moment exceeds the set threshold:

[0114] When the change amplitude does not exceed the threshold, the update module is triggered;

[0115] When the change amplitude exceeds the threshold, the evaluation module is triggered;

[0116] An update module is used to determine whether the monitoring frequency data at the current moment is normal, and to perform weighted processing on the monitoring frequency data at the current moment and the stored background frequency data at the current moment to obtain the background frequency data at the next moment, and to update the background frequency data at the next moment to the background frequency data set, and to continue the monitoring signal analysis at the next moment;

[0117] The evaluation module is used to evaluate the current monitoring frequency data without updating the background frequency data: if the change amplitude exceeds the threshold value intermittently or occasionally, the current monitoring frequency data is judged to be normal, the current monitoring data is ignored, and the monitoring signal analysis of the next moment is continued; if the change amplitude exceeds the threshold value continuously or occurs multiple times at intervals, the current monitoring frequency data is judged to be abnormal and an abnormal signal is output;

[0118] Early warning module: used to determine the location of micro-earthquakes based on input abnormal signals using positioning technology and send early warning signals to the location of the micro-earthquakes;

[0119] The background field frequency point dataset is used to store updated background field frequency point data.

[0120] The mine earthquake early warning system designed in this invention uses Power over Ethernet (PoE) to enhance system security, eliminating the need for high-voltage power distribution, thus improving safety. Furthermore, the centralized power supply is more stable than distributed power supply. The system is simple and easy to use, as network terminals require no external power supply, requiring only network cables. This system is cost-effective, eliminating the need for power cables, socket locations, and wiring modifications, saving installation time and minimizing construction and maintenance costs. Furthermore, the use of a 3-axis MEMS accelerometer improves resolution, enabling detection of the terminal's inclination angle at a finer scale, reducing the load on the main processor and overall system power consumption.

[0121] Compared with the prior art, the monitoring and early warning method of the present invention, by updating background field frequency data in real time, can ignore other relatively gentle background field changes except for sudden microseismic events during monitoring, and promptly incorporates minor changes that have already occurred into the background field, providing a relatively stable background field data for real-time microseismic monitoring signal analysis, achieving the effect of continuously suppressing noise, making the evaluation of microseismic signals more accurate, and enabling real-time and accurate monitoring of mining earthquakes occurring in a designated area, thereby reducing the occurrence of false microseismic early warning signals. Furthermore, by performing time-varying correction on the acquired monitoring signals, the present invention calibrates data collected on different dates to the same baseline level, eliminating slow changes in geological tectonic movement strata that are not microseismic events during monitoring. This ensures that microseismic events can be detected while preventing tectonic changes accumulated over a period of time from triggering false monitoring alarms. This reduces the impact of changes in geological background field noise signals caused by natural geological background changes during the acquisition process on real-time acquired microseismic signals, thereby improving the quality of the acquired microseismic signals. By performing global consistency correction on the signal collectors, systematic errors caused by collector differences can be eliminated, making subsequent signal processing and evaluation more accurate, thereby achieving advantages.

[0122] By combining the above technologies, the present invention can overcome the problems of weak time domain microseismic signals collected in traditional microseismic monitoring, susceptibility to various interferences, and inaccurate positioning. While ensuring accurate early warning of microseismic events, it can effectively avoid misidentifying non-microseismic events as microseismic events, and can better monitor possible mining earthquake events in designated areas in real time, quickly, and accurately.

[0123] The above-described embodiments merely represent several implementations of the present invention. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous modifications and improvements without departing from the spirit of the present invention, and the present invention is intended to encompass such modifications and variations.

Claims

1. A mine earthquake early warning method based on microseismic monitoring, characterized in that: The following steps are involved: S10 converts the input current monitoring signal from the time domain to the frequency domain to obtain the current monitoring frequency data; S20 determines whether the current monitoring frequency data is normal based on whether the change amplitude between the energy value of the current monitoring frequency data and the energy value of the stored background field frequency data at the current moment exceeds a set threshold: When the change amplitude does not exceed the threshold, executing step S30; When the change amplitude exceeds the threshold, step S40 is executed; S30 determines that the monitoring frequency data at the current moment is normal, and performs weighted processing on the monitoring frequency data at the current moment and the stored background frequency data at the current moment to obtain the background frequency data at the next moment, and updates the background frequency data at the next moment to the background frequency data set, and continues the monitoring signal analysis at the next moment; S40 does not update the background frequency data and evaluates the monitoring frequency data at the current moment: if the change amplitude exceeds the threshold value, it is intermittent or occurs occasionally, and the monitoring frequency data at the current moment is determined to be normal, and the monitoring data at the current moment is ignored, and the monitoring signal analysis at the next moment is continued; If the change amplitude exceeds the threshold value continuously or occurs multiple times at intervals, the monitoring frequency data at the current moment is judged to be abnormal and an abnormal signal is output; S50 uses positioning technology to determine the location of the micro-earthquake based on the input abnormal signal and sends an early warning signal to the place where the micro-earthquake occurred.

2. The mine earthquake early warning method according to claim 1, characterized in that: The background field frequency data is obtained by: S21 obtains initial background field frequency point data: performs Fourier transform on the monitoring signals collected during a certain period of time without microseismic events in the early stage to obtain initial background field frequency point data; S22 obtains the background field frequency data at the current moment: the monitoring frequency data at the previous moment and the background field frequency data at the previous moment are weighted averaged to obtain the background field frequency data at the current moment, which is expressed as: in, Indicates the background frequency data at the current moment. Indicates the background frequency data at the previous moment, Indicates the monitoring frequency data at the last moment.

3. The mine earthquake early warning method according to claim 1, characterized in that: The calculation method for the change amplitude between the energy value of the monitoring frequency data at the current moment and the energy value of the stored background frequency data at the current moment is: in, Indicates the energy value of the frequency point data monitored at the current moment. Indicates the energy value of the background field frequency data at the current moment.

4. The mine earthquake early warning method according to any one of claims 1 to 3, characterized in that: Before converting the input current-time monitoring signal from the time domain to the frequency domain, the method further includes performing point-by-point time-varying correction on the current-time monitoring signal using the input timing geological background field noise signal, wherein the current-time monitoring signal after time-varying correction satisfies the following relationship: in, is the current monitoring signal after time-varying correction, is the monitoring signal at the current moment, R (t′-1)～t′ It is the time-varying correction from the previous period to the current period.

5. The mine earthquake early warning method according to claim 4, characterized in that: The time-varying correction value R from the previous period to the current period (t′-1)～t′ Satisfies the following relationship: in, is the amplitude sequence of the geological background noise signal in the initial period, is the amplitude sequence of the geological background field noise signal in the previous period.

6. A mine earthquake early warning system based on microseismic monitoring, comprising a plurality of data acquisition units, a data exchange unit and a monitoring host, characterized in that: The signals collected by the data acquisition unit are transmitted to the monitoring host via the data exchange unit, and the monitoring host executes the steps of the mine earthquake early warning method based on microseismic monitoring as described in any one of claims 1 to 5.

7. The mine earthquake early warning system according to claim 6, characterized in that: The data acquisition unit includes a plurality of signal collectors and a POE power supply for supplying power to the signal collectors.

8. The mine earthquake early warning system according to claim 7, characterized in that: Performing global consistency correction on the signal collector to obtain a global consistency correction coefficient of the signal collector.

9. The mine earthquake early warning system according to claim 8, characterized in that: The global consistency correction coefficient is obtained by: All signal collectors are placed at the same point to collect data for a period of time, and the average signal amplitude of each signal collector and the average signal amplitude of all signal collectors are obtained; Calculate the ratio of the average amplitude of all signal collectors to the average amplitude of each signal collector to obtain the global consistency correction coefficient c of each signal collector. i , whose expression is: Where E is the average amplitude of all signal collectors, is the average amplitude of the i-th signal collector, A i [x j ] is the amplitude sequence of the signal collected by the i-th signal collector, m is the number of signals collected by the i-th signal collector, and n is the number of signal collectors.

10. A mine earthquake early warning device based on microseismic monitoring, comprising: Data conversion module: used to convert the input current monitoring signal from the time domain to the frequency domain to obtain the current monitoring frequency data; Judgment module: used to judge whether the current monitoring frequency data is normal based on whether the change amplitude of the energy value of the current monitoring frequency data and the energy value of the stored background field frequency data at the current moment exceeds the set threshold: When the change amplitude does not exceed the threshold, the update module is triggered; When the change amplitude exceeds the threshold, the evaluation module is triggered; An update module is used to determine whether the monitoring frequency data at the current moment is normal, and to perform weighted processing on the monitoring frequency data at the current moment and the stored background frequency data at the current moment to obtain the background frequency data at the next moment, and to update the background frequency data at the next moment to the background frequency data set, and to continue the monitoring signal analysis at the next moment; The evaluation module is used to evaluate the current monitoring frequency data without updating the background frequency data: if the change amplitude exceeds the threshold, it is intermittent or accidental, and the current monitoring frequency data is judged to be normal, the current monitoring data is ignored, and the monitoring signal analysis of the next moment is continued; If the change amplitude exceeds the threshold value continuously or occurs multiple times at intervals, the monitoring frequency data at the current moment is judged to be abnormal and an abnormal signal is output; Early warning module: used to determine the location of micro-earthquakes based on input abnormal signals using positioning technology and send early warning signals to the location of the micro-earthquakes; The background field frequency point dataset is used to store updated background field frequency point data.

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